code: def test_case_where_n_is_bigger_than_hypothesis_length(self):
      # Test BLEU to nth order of n-grams, where n > len(hypothesis).
      references = ["John loves Mary ?".split()]
      hypothesis = "John loves Mary".split()
      n = len(hypothesis) + 1  #
      weights = (1.0 / n,) * n  # Uniform weights.
      # Since no n-grams matches were found the result should be zero
      # exp(w_1 * 1 * w_2 * 1 * w_3 * 1 * w_4 * -inf) = 0
      self.assertAlmostEqual(
          sentence_bleu(references, hypothesis, weights), 0.0, places=4
      )
      # Checks that the warning has been raised because len(hypothesis) < 4.
      try:
          self.assertWarns(
              UserWarning, sentence_bleu, references, hypothesis
          )
      except AttributeError:
          pass  # unittest.TestCase.assertWarns is only supported in Python >= 3.2.
  
      # Test case where n > len(hypothesis) but so is n > len(reference), and
      # it's a special case where reference == hypothesis.
      references = ["John loves Mary".split()]
      hypothesis = "John loves Mary".split()
      # Since no 4-grams matches were found the result should be zero
      # exp(w_1 * 1 * w_2 * 1 * w_3 * 1 * w_4 * -inf) = 0
      self.assertAlmostEqual(
          sentence_bleu(references, hypothesis, weights), 0.0, places=4
      )
  
imports: import unittest
  import numpy
  from nltk.data import find
  from nltk.translate.bleu_score import SmoothingFunction, brevity_penalty, closest_ref_length, corpus_bleu, modified_precision, sentence_bleu
label_desc: Use image node_id 1 for calling the TestBLEUFringeCases obj's underlying member method code with example usage: obj.test_case_where_n_is_bigger_than_hypothesis_length() without return types